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Perception for collision avoidance and autonomous driving
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DOI：10.1016/S0957-4158(03)00047-3.png)
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The Navlab group at Carnegie Mellon University has a long history of development of automated vehicles and intelligent systems for driver assistance. The earlier work of the group concentrated on road following, cross-country driving, and obstacle detection. The new focus is on short-range sensing, to look all around the vehicle for safe driving. The current system uses video sensing, laser rangefinders, a novel light-stripe rangefinder, software to process each sensor individually, a map-based fusion system, and a probability based predictive model. The complete system has been demonstrated on the Navlab I I vehicle for monitoring the environment of a vehicle driving through a cluttered urban environment, detecting and tracking fixed objects, moving objects, pedestrians, curbs, and roads. (C) 2003 Elsevier Ltd. All rights reserved.
Keyword:
collision avoidance
autonomous driving
short-range surround sensing
optical flow
triangulation laser sensor
curb detection
LIDAR object detection
sensor fusion
collision prediction
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